{"id":"W1960233492","doi":"10.1109/icassp.1988.196780","title":"Estimation of image motion fields: Bayesian formulation and stochastic solution","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Maximum a posteriori estimation; Markov random field; Motion estimation; Random field; Artificial intelligence; Markov chain; Motion field; Computer science; Prior probability; Markov process; Stochastic process; Mathematics; Bayesian probability; Mathematical optimization; Image (mathematics); Machine learning; Image segmentation; Statistics; Maximum likelihood","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001415859,0.001030617,0.0009790582,0.001497168,0.000431473,0.001597207,0.001524991,0.00246459,0.002409225],"category_scores_gemma":[0.004350874,0.001060638,0.001105161,0.001685948,0.001436314,0.001990088,0.001393773,0.001623086,0.0008189284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001261431,"about_ca_system_score_gemma":0.001193414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005835082,"about_ca_topic_score_gemma":0.005891161,"domain_scores_codex":[0.9994943,0.0001680072,0.0000287974,0.00009401044,0.000185756,0.0000290942],"domain_scores_gemma":[0.9990014,0.0006748979,0.0001292371,0.00004547699,0.0001180678,0.00003093699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002360666,0.00002710112,0.0003480893,0.0001962038,0.0000712671,0.0001254288,0.00009699695,0.6847211,0.002922158,0.2282423,0.003591123,0.07963474],"study_design_scores_gemma":[0.000007272338,0.00001024313,0.0001191905,0.00002654599,0.000008491651,0.00004708525,0.00000691505,0.9317389,0.0005667165,0.06408524,0.003365439,0.00001802548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003415466,0.0001779833,0.9987759,0.0001654059,0.00001303188,0.00001149684,0.00002681931,0.00004299037,0.0004448337],"genre_scores_gemma":[0.08164825,0.002636964,0.906667,0.0002904683,0.0003543284,0.0004080433,0.0005130588,0.0002341764,0.007247676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005835082,"threshold_uncertainty_score":0.01160222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058937815170449,"score_gpt":0.2690725991266554,"score_spread":0.2584832209749509,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}